Abstract #3410
MRI Constrained Reconstruction without Tuning Parameters Using ADMM and Morozov's Discrepency Principle
Weiyi Chen 1 , Yi Guo 1 , Ziyue Wu 2 , and Krishna S. Nayak 1,2
1
Electrical Engineering, University of
Southern California, Los Angeles, CA, United States,
2
Biomedical
Engineering, University of Southern California, Los
Angeles, CA, United States
We propose a method for MRI constrained reconstruction
using ADMM framework that is data-driven, and does not
require manual selection of tuning parameters. We use
Morozov's discrepancy principle as a criterion to
iteratively determine the tuning parameter. Tests with
T2w brain data show that the reconstruction quality is
comparable with reconstructions using manually selected
parameter.
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